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Data and the circular economy: why engineers need to start speaking a common language

Sweco author: Andrew Krebs, Building Performance Digital Manager

For me, circular success all comes back to the data. I am a digital engineer, so without the data that underpins my decision-making at all stages of a project, I am shooting blind and I cannot say that my decisions are anything other than guesswork informed by my past experiences.

There is a vital feedback loop in the construction process, which at the moment is rather slow and, in some quarters, almost broken. This is highlighted by the Catch-22 situation whereby on one hand engineers do not want to put too much definitive detail in their stage 2-3 models for good and sound engineering reasons, but on the other want to collaborate with the need for more granular information to enable as-accurate-as-possible cost estimates sought by Quantity Surveyors, other stakeholders in the engineering ecosystem and of course the clients themselves.

Currently, designers design those stages to a zonal level of definition, meaning that QS’s must use rules of thumb and (albeit often educated) guesstimates to build an indicative idea of what costs will be. This then sets the project up to succeed or fail based on how ‘lucky’ these methods prove to be.

Many in the trade would no doubt object rather vigorously to my inference there, but I would counter that any detailed analysis of where the cost data, at these stages, comes from currently would make it difficult to argue in the contrary.

To be clear, the reason for this less-than-perfect process is not laziness, nor negligence or any lack of desire to get it right. Far from it. It is that the real world today is full of buildings which all talk different languages, which contain items that are basically the same, but which are either not able to communicate with the outside world, or which do so in a proprietary language which is different to the building across the road, or the similar building in another city, losing the ability to compare performance in each and learn from the findings.

The same engineering concept (heat load, for example) can be called a dozen different things in a dozen different buildings as you walk up a street depending on who designed the systems, which manufacturer’s systems are installed and which CAFM system is trying to make sense of it all.

This commentary may not seem all too closely connected to the circular economy. But the state-of-the-nation in how data is used – or not – sits undeniably at the root of enabling the design, procurement and commissioning of any building which hopes to participate in and drive a truly circular economy. The trick lies in finding a way to link this in people’s minds when we seek to engage in circularity. We cannot just start “doing circular” in the same way

we have perpetuated the linear economy up to now. We need to first lay the foundations in place to allow better planning, insight and decision making before we arrive at the point where we can transition effectively.

The first step to that foundation is having a common data language across the built environment – with the same building phenomena being called the same thing. So heat load is heat load, real power is real power and area is area. Not “heating load”, “P” and “overall area” or other derivative labels. Digital tools can only be deployed consistently when a programme, robot or algorithm knows, singularly, what it is looking for.

If everything has a common, structured name (E.g. based on a common language such as the CIBSE Product Data Templates), we can tap into the built environment and see how things are performing at any given time, in any given place…free of ambiguity or doubt.

This is where we might fix that broken feedback loop I mentioned earlier. With commonality, we will be able to see how things are actually happening in buildings, we will be able to collect anonymised data in a central, non-commercial (ie impartial) repository (the engineering institutions for example) and use that to inform the rules of thumb that we all use at early stages of a build.

Syntax can be updated to reflect what is happening today, not what happened 20 years ago. We can then, instead of saying that “Schools need X and Y” start to recognise that a school on the North East coast of Scotland needs somewhat different arrangements than one in the Peak District, where the social, climate and topographical variables differ. This data set will enable us to start to design and build for the evidenced needs of a site’s local area, not the generic expectations of the function of the building.

The good news is that this is already starting to happen:

PAS 14191 is a standard which data dictionaries should adhere to which means that they will be interoperable and we can read into them.

The Lexicon Project led by the Construction Products Association is leading the way in creating a consistent set of product data templates and product data sheets to allow consistent naming of both products and the parameters which go into defining how those products are formed and how they operate.

The CIBSE BIMHawk is an already functioning version of this, which was a precursor to Lexicon but which is fully integrated into the principles of Lexicon, which has a wide range of product data templates available for building services equipment.

To enable and promote circularity, Sweco and our peers must place ourselves firmly behind the creation of a common data structure for the industry. It will underpin all the fancy technical things we need to do and which other, cleverer people than me are better qualified to talk about – perhaps an article for another day from one of my esteemed colleagues.

This year, I will be the chair of the Society of Digital Engineering, and I will seek to advocate common data language and in turn a circular mindset as I pool insights with the industry leaders. If you would like to join the conversation and discuss how digital transformation can help us evolve as an industry, please do get in touch below.



Building the future through circular data: tools for mining the ‘green gold’